code: def preprocess():
      FLAGS = ReArgsParser().parse_args()
      config = load_config(FLAGS.config)
      config = merge_config(config, FLAGS.opt)
  
      ser_config = load_config(FLAGS.config_ser)
      ser_config = merge_config(ser_config, FLAGS.opt_ser)
  
      logger = get_logger()
  
      # check if set use_gpu=True in paddlepaddle cpu version
      use_gpu = config["Global"]["use_gpu"]
  
      device = (
          "gpu:{}".format(dist.ParallelEnv().dev_id)
          if use_gpu
          else "cpu"
      )
      device = paddle.set_device(device)
  
      logger.info("{} re config {}".format("*" * 10, "*" * 10))
      print_dict(config, logger)
      logger.info("\n")
      logger.info("{} ser config {}".format("*" * 10, "*" * 10))
      print_dict(ser_config, logger)
      logger.info(
          "train with paddle {} and device {}".format(
              paddle.__version__, device
          )
      )
      return config, ser_config, device, logger
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import numpy
  import os
  import sys
  import cv2
  import json
  import paddle
  import paddle.distributed
  from ppocr.data import create_operators, transform
  from ppocr.modeling.architectures import build_model
  from ppocr.postprocess import build_post_process
  from ppocr.utils.save_load import load_model
  from ppocr.utils.visual import draw_re_results
  from ppocr.utils.logging import get_logger
  from ppocr.utils.utility import get_image_file_list, load_vqa_bio_label_maps, print_dict
  from tools.program import ArgsParser, load_config, merge_config
  from tools.infer_kie_token_ser import SerPredictor
label_desc: Use image node_id 2 for calling a global function with example usage: preprocess() and returns: config,  ser_config,  device,  logger